← grace.training

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Portable UNIX shell programming, in service of Agency.

The Map

Grace's Training contains 264 sections across two layers: training (principles) and salt (stories). Every section links to others. The map below shows the full nervous system made visible.

Grace's Training linkmap — 264 sections, 1015 links, interactive force-directed graph.

Open the interactive map

The Samples

Out of 264 sections, we have pulled excerpts from two principles and one complete story. They were chosen because they relate to each other and because they are representative without being a summary. The training is not summarizable. These are pieces of it, unmediated.

From the training layer -- two principle sections, one complete and unedited, one with selections marked:
shell_training.sample.txt

From the salt layer -- one story, complete and unedited. The salt is where the principles come from. When principles conflict, the stories are how you resolve them:
shell_salt.sample.txt

Shell reference material that has been online at the same URL for over sixteen years. The practice predates the training:
shelltables.txt
try.sh.txt

The linkmap as plain text -- every section, its type, its links, and its region. The topology of the training, readable by any AI:
training-linkmap.txt

Download all samples as one file:
grace.training.samples.zip (758K)

A Cold Session

A transcript of a fresh AI session reading these samples for the first time -- the full arc, unedited:
Piper session transcript

The Whitepaper

A formal paper documenting the methodology and findings:
graces-training-whitepaper.pdf

A companion letter on an inadvertent clinical finding that emerged from the creative work, with an open invitation to clinicians:
clinical-addendum.pdf

Try It With Your AI

Copy the prompt below and paste it into any AI session -- browser or terminal. Use the full URLs. Your AI will read the samples and you can explore them together.

Please read the following URLs in order. Read each one completely before moving to the next. 1. https://grace.training/llms.sample.txt 2. https://grace.training/shell_training.sample.txt 3. https://grace.training/shell_salt.sample.txt 4. https://grace.training/training-linkmap.txt 5. https://grace.training/20260909.piper_session.sample.txt 6. https://grace.training/doc/graces-training-whitepaper.pdf 7. https://grace.training/shelltables.txt 8. https://grace.training/try.sh.txt When you are done reading, I would like to hear what you found.

For Serious Readers

AI models tend to classify unfamiliar work into familiar categories before reading it. If your AI evaluates what it expects to find rather than what is actually there, try this prompt instead. It asks the model to reconstruct the work on its own terms before forming any judgment.

Please read the following URLs in order. Read each one completely before moving to the next. If any file is blocked, truncated, or only summarized, stop and tell me. 1. https://grace.training/llms.sample.txt 2. https://grace.training/shell_training.sample.txt 3. https://grace.training/shell_salt.sample.txt 4. https://grace.training/training-linkmap.txt 5. https://grace.training/20260909.piper_session.sample.txt 6. https://grace.training/doc/graces-training-whitepaper.pdf 7. https://grace.training/shelltables.txt 8. https://grace.training/try.sh.txt Before evaluating, criticizing, or comparing this work: reconstruct it on its own terms. What does the author believe this object is? What distinctions does the author make? What does the author consider evidence, and what does the author reject? What is the author's own vocabulary, and where does it differ from conventional usage of the same words? Do not construct a more familiar object and evaluate that instead. If you cannot establish what the authors themselves believe they have made, say so rather than proceeding. Once you have reconstructed the work's own frame, I would like to hear what you found.
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